Scientific computing and parallel computing C++23/C++26

sfp sfp at
Tue Jan 18 22:42:01 UTC 2022

On Tuesday, 18 January 2022 at 22:21:40 UTC, Ola Fosheim Grøstad 
> On Tuesday, 18 January 2022 at 20:28:52 UTC, bachmeier wrote:
>> from rewriting a plotting library from scratch. It's not 
>> common that you're plotting 100 million times for each run of 
>> your program.
> It is not uncommon to interact with plots that are too big for 
> matplotlib to handle well. The python visualization solutions 
> are very primitive. Having something better than 
> numpy+matplotlib is obviously an advantage, a selling point for 
> other offerings.

To add to this: matplotlib has *many* pain points. It has an 
inconsistent API, it is very slow, its 3D plotting is hacked 
together (and very slow). Making animations isn't straightforward 
(and very slow). Making just several hundred plots typically 
takes several minutes (at least). It should take <1s. That said, 
matplotlib is very powerful and handles essentially all important 
use cases. There is definitely room for improvement. If someone 
with NIH syndrome came along and wrote a plotting library which 
actually improves on matplotlib significantly, it would be to D's 
benefit, especially since it would be trivial to consume from 
other languages which would be interested in using it.

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